{"cells":[{"cell_type":"code","execution_count":1,"source":["import tensorflow as tf\n","from tensorflow import keras\n","import numpy as np\n","import matplotlib.pyplot as plt\n","\n","\n","fashion_mnist = keras.datasets.fashion_mnist\n","(train_images, train_labels), (test_images, test_labels) = fashion_mnist.load_data()\n","class_names = ['T-shirt/top', 'Trouser', 'Pullover', 'Dress', 'Coat','Sandal', 'Shirt', 'Sneaker', 'Bag', 'Ankle boot']\n","'''\n","0\tT恤/上衣\n","1\t裤子\n","2\t套头衫\n","3\t连衣裙\n","4\t外套\n","5\t凉鞋\n","6\t衬衫\n","7\t运动鞋\n","8\t包\n","9\t短靴'''\n","train_images = train_images / 255.0\n","test_images = test_images / 255.0#将这些值缩小至 0 到 1 之间，然后将其馈送到神经网络模型。为此，请将这些值除以 255。请务必以相同的方式对训练集和测试集进行预处理：\n","model = keras.Sequential([\n","    keras.layers.Flatten(input_shape=(28, 28)),\n","    keras.layers.Dense(128, activation='relu'),\n","    keras.layers.Dense(10),\n","    keras.layers.Softmax()\n","])\n","'''该网络的第一层 tf.keras.layers.Flatten 将图像格式从二维数组（28 x 28 像素）转换成一维数组（28 x 28 = 784 像素）。\n","将该层视为图像中未堆叠的像素行并将其排列起来。该层没有要学习的参数，它只会重新格式化数据。\n","展平像素后，网络会包括两个 tf.keras.layers.Dense 层的序列。它们是密集连接或全连接神经层。\n","第一个 Dense 层有 128 个节点（或神经元）。第二个（也是最后一个）层会返回一个长度为 10 的 logits 数组。\n","每个节点都包含一个得分，用来表示当前图像属于 10 个类中的哪一类。'''\n","model.compile(optimizer='adam',\n","              loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),\n","              metrics=['accuracy'])\n","model.fit(train_images, train_labels, epochs=10)\n","\n","predictions = model.predict(test_images)\n","predictions[0]"],"outputs":[{"output_type":"stream","name":"stdout","text":["Epoch 1/10\n","1875/1875 [==============================] - 10s 5ms/step - loss: 1.7122 - accuracy: 0.7562\n","Epoch 2/10\n","1875/1875 [==============================] - 9s 5ms/step - loss: 1.6753 - accuracy: 0.7872\n","Epoch 3/10\n","1875/1875 [==============================] - 9s 5ms/step - loss: 1.6650 - accuracy: 0.7973\n","Epoch 4/10\n","1875/1875 [==============================] - 10s 5ms/step - loss: 1.6587 - accuracy: 0.8028\n","Epoch 5/10\n","1875/1875 [==============================] - 10s 5ms/step - loss: 1.6546 - accuracy: 0.8069\n","Epoch 6/10\n","1875/1875 [==============================] - 10s 5ms/step - loss: 1.6512 - accuracy: 0.8105\n","Epoch 7/10\n","1875/1875 [==============================] - 10s 5ms/step - loss: 1.6484 - accuracy: 0.8128\n","Epoch 8/10\n","1875/1875 [==============================] - 10s 6ms/step - loss: 1.6454 - accuracy: 0.8160\n","Epoch 9/10\n","1875/1875 [==============================] - 11s 6ms/step - loss: 1.6430 - accuracy: 0.8182\n","Epoch 10/10\n","1875/1875 [==============================] - 10s 6ms/step - loss: 1.5949 - accuracy: 0.8664\n"]},{"output_type":"execute_result","data":{"text/plain":["array([5.0362031e-13, 4.2485886e-18, 8.7263304e-16, 1.4762487e-17,\n","       3.5188266e-14, 2.4597635e-04, 3.5841528e-14, 9.4832281e-08,\n","       9.3014901e-12, 9.9975389e-01], dtype=float32)"]},"metadata":{},"execution_count":1}],"metadata":{}},{"cell_type":"code","execution_count":2,"source":["np.argmax(predictions[0])"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["9"]},"metadata":{},"execution_count":2}],"metadata":{}},{"cell_type":"code","execution_count":3,"source":["test_labels[0]"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["9"]},"metadata":{},"execution_count":3}],"metadata":{}},{"cell_type":"code","execution_count":5,"source":["def plot_image(i, predictions_array, true_label, img):\n","  predictions_array, true_label, img = predictions_array, true_label[i], img[i]\n","  plt.grid(False)\n","  plt.xticks([])\n","  plt.yticks([])\n","\n","  plt.imshow(img, cmap=plt.cm.binary)\n","\n","  predicted_label = np.argmax(predictions_array)\n","  if predicted_label == true_label:\n","    color = 'blue'\n","  else:\n","    color = 'red'\n","\n","  plt.xlabel(\"{} {:2.0f}% ({})\".format(class_names[predicted_label],\n","                                100*np.max(predictions_array),\n","                                class_names[true_label]),\n","                                color=color)\n","\n","def plot_value_array(i, predictions_array, true_label):\n","  predictions_array, true_label = predictions_array, true_label[i]\n","  plt.grid(False)\n","  plt.xticks(range(10))\n","  plt.yticks([])\n","  thisplot = plt.bar(range(10), predictions_array, color=\"#777777\")\n","  plt.ylim([0, 1])\n","  predicted_label = np.argmax(predictions_array)\n","\n","  thisplot[predicted_label].set_color('red')\n","  thisplot[true_label].set_color('blue')"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":6,"source":["i = 0\n","plt.figure(figsize=(6,3))\n","plt.subplot(1,2,1)\n","plot_image(i, predictions[i], test_labels, test_images)\n","plt.subplot(1,2,2)\n","plot_value_array(i, predictions[i],  test_labels)\n","plt.show()"],"outputs":[{"output_type":"display_data","data":{"image/png":"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","text/plain":["<Figure size 432x216 with 2 Axes>"]},"metadata":{"needs_background":"light"}}],"metadata":{}},{"cell_type":"code","execution_count":7,"source":["num_rows = 5\n","num_cols = 3\n","num_images = num_rows*num_cols\n","plt.figure(figsize=(2*2*num_cols, 2*num_rows))\n","for i in range(num_images):\n","  plt.subplot(num_rows, 2*num_cols, 2*i+1)\n","  plot_image(i, predictions[i], test_labels, test_images)\n","  plt.subplot(num_rows, 2*num_cols, 2*i+2)\n","  plot_value_array(i, predictions[i], test_labels)\n","plt.tight_layout()\n","plt.show()"],"outputs":[{"output_type":"display_data","data":{"image/png":"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","text/plain":["<Figure size 864x720 with 30 Axes>"]},"metadata":{"needs_background":"light"}}],"metadata":{}}],"nbformat":4,"nbformat_minor":2,"metadata":{"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":3},"orig_nbformat":4}}